Full text: XVIIIth Congress (Part B3)

   
  
   
  
   
   
    
  
   
   
   
   
   
  
  
   
    
  
  
    
  
   
   
   
  
  
   
  
  
   
   
   
   
   
  
  
   
   
   
    
  
  
   
   
  
  
   
   
   
  
  
  
  
  
   
  
   
  
  
  
   
  
   
  
   
   
   
   
   
   
      
  
Analysis (Ie) 
  
g of Blobs (I3) 
  
sult 
4.5 Further Steps 
Future analyzing of the type of hatched patterns (diagonal 
or parallel) will enable the determination of the use of build- 
ings (residential buildings or outbuildings) besides the pure 
location information. 
Further steps will be the elimination of remaining errors as 
well as the hatching lines. This way the final vectorization 
only will have to deal with the empty outlines of the buildings. 
Concerning the building outlines, it is planned not only to ex- 
tract the outer boundaries (transition of blobs to background) 
but also to extract the inner boundaries between adjacent 
houses. However, the latter task will be more complicated. 
Furthermore, the addition of two more analysis directions, 
the diagonals, in terms of the investigation of the runlength 
encoded vectors is planned. That will probably reduce ambi- 
guities and make the results more robust. 
Additionally, it has to be thought of relating the empirically 
found dimensions of the structuring elements to the scanning 
resolution and to different line widths. Possibilities of includ- 
ing algorithms for assessing the obtained results should be 
included. 
5 CONCLUSIONS 
The paper demonstrates a procedure for a raster based, au- 
tomated recognition process of buildings within the german 
base map 1:5000. The identification of the buildings includes 
the recognition of the hatched filling patterns as well as the 
outlines of the buildings. Although the results represent a 
preliminary stage, they show the general potential of raster 
based techniques, such as mathematical morphology, for au- 
tomated map understanding tasks. 
The advantages of the introduced raster based approach can 
be summarized in the following way: 
— low complexity of the approach 
— maintenance of the positional accuracy because of the 
acting on the original image data up to an advanced 
processing stage 
— strongly reduced amount of vector data. 
Since an enormous amount of digital building data has to be 
captured, e.g. for the creation of 3D models of towns, the 
proposed approach is a useful tool to obtain the 2D outlines 
of buildings as vector representations in an efficient way. 
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